code: def args_str(args):
      # a debug helper
      if torch.is_tensor(args):
          return f"T[{args.shape}]"
      elif isinstance(args, tuple):
          return f"tuple({', '.join([args_str(x) for x in args])})"
      elif isinstance(args, list):
          return f"list({', '.join([args_str(x) for x in args])})"
      else:
          return str(args)
  
file_path: pytorch/torch/_dynamo/backends/distributed.py
imports: import logging
  import traceback
  from dataclasses import dataclass, field
  from typing import Any, List, Optional
  import torch
  from torch import fx
  from torch._dynamo.output_graph import GraphCompileReason
  from torch._dynamo.utils import deepcopy_to_fake_tensor, detect_fake_mode
  from torch.fx.node import Node
label_desc: Use image node_id 1 for calling a global function with example usage: args_str(args) and returns: str, args, str, str, str, str, str, str, str, str